Operational, gauge-free quantum tomography

Author:

Di Matteo Olivia123,Gamble John4,Granade Chris4,Rudinger Kenneth5,Wiebe Nathan467

Affiliation:

1. TRIUMF, Vancouver, British Columbia, Canada V6T2A3

2. Department of Physics and Astronomy, University of Waterloo, Waterloo, ON, Canada

3. Institute for Quantum Computing, University of Waterloo, Waterloo, ON, Canada

4. Microsoft Research, Quantum Architectures and Computation Group, Redmond, Washington 98052, USA

5. Quantum Performance Laboratory, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA

6. Department of Physics, University of Washington, Seattle, WA 98195, USA

7. Pacific Northwest National Laboratory, Richland, WA 99352, USA

Abstract

As increasingly impressive quantum information processors are realized in laboratories around the world, robust and reliable characterization of these devices is now more urgent than ever. These diagnostics can take many forms, but one of the most popular categories istomography, where an underlying parameterized model is proposed for a device and inferred by experiments. Here, we introduce and implement efficient operational tomography, which uses experimental observables as these model parameters. This addresses a problem of ambiguity in representation that arises in current tomographic approaches (thegauge problem). Solving the gauge problem enables us to efficiently implement operational tomography in a Bayesian framework computationally, and hence gives us a natural way to include prior information and discuss uncertainty in fit parameters. We demonstrate this new tomography in a variety of different experimentally-relevant scenarios, including standard process tomography, Ramsey interferometry, randomized benchmarking, and gate set tomography.

Publisher

Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften

Subject

Physics and Astronomy (miscellaneous),Atomic and Molecular Physics, and Optics

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Universal framework for simultaneous tomography of quantum states and SPAM noise;Quantum;2024-07-30

2. General Algorithms for SPAM Noise Characterization;2023 IEEE International Conference on Quantum Computing and Engineering (QCE);2023-09-17

3. Streaming Quantum Gate Set Tomography Using the Extended Kalman Filter;2023 IEEE International Conference on Quantum Computing and Engineering (QCE);2023-09-17

4. Gradient-Descent Quantum Process Tomography by Learning Kraus Operators;Physical Review Letters;2023-04-14

5. Quantum Simulation of Dissipative Collective Effects on Noisy Quantum Computers;PRX Quantum;2023-03-08

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